Seasonality of Precipitation over Himalayan Watersheds in CORDEX South Asia and their Driving CMIP5 Experiments

Water Quality Criteria and Ecological Risk Assessment of Typical Transition Metals in South Asia

Transition metal pollution in rivers in South Asia is more serious than in other regions because of the lack of adequate freshwater management measures. Water quality criteria (WQC) for South Asia is urgently needed to protect regional aquatic environments because of the occurrence of transboundary rivers. The present study established non-parametric kernel density estimation species sensitivity distribution (NPKDE-SSD) models and then derived the acceptable hazardous concentration for protection of 95% of all aquatic species (HC5) and WQC of six typical transition metals in South Asia. The results showed that the order of acute and chronic WQC was Mn > Fe > Cd > Zn > Cu > Hg and Cu > Fe > Cd, respectively. A risk assessment of these metals in the Indus River, the Ganges River, the Brahmaputra River, the Meghna River, and the Bagmati River was also carried out. Based on the results, these major rivers in South Asia were highly polluted with transition metals, with significant ecological risks for a large number of aquatic species. This study can contribute to a better understanding of ecological risks in South Asia and provide a scientific basis for the updating of water quality standards and the increase in overall water quality.

Evaluating the added values of regional climate modeling over China at different resolutions

Previous studies have suggested that dynamical downscaling to global climate models can produce improved climate simulations at regional and local scales. However, the expensive computational requirements of dynamical downscaling inevitably add a limit to the spatial resolution of the resulting regional climate simulations. In order to find a balance between computational requirements and simulation improvements, it is extremely important to investigate how the spatial resolution of regional climate simulation affects the added values of dynamical downscaling; yet, it is still not well understood. Therefore, in this study, we conduct long-term climate simulations for the entire country of China with the PRECIS regional climate model at two different spatial resolutions (i.e., 25 and 50 km). The purpose is to evaluate whether a fine-resolution model simulation, given its considerable requirements for computational resources, would add more valuable information for understanding regional climatology than a coarse-resolution model simulation. Our results show that the PRECIS can reasonably reproduce the spatial distribution of seasonal and monthly mean temperature and precipitation over the most of regions in China. However, in the process of downscaling, RCM with higher resolution cannot always produce more accurate output. In regard to precipitation simulations, compared with the host GCM, it is difficult to determine exactly a homogeneous improvement of performance in downscaling, both in terms of spatial patterns as well as magnitude of errors. For interannual variability, variations in temperature are closer to observation than precipitation and the high-resolution R25 has better skills over the northwest than R50. Moreover, except for the west, it is shown that PRECIS is able to better reproduce the probability distribution function of precipitation and some impact-relevant indices such as the number of consecutive wet days and simple precipitation intensity index in spatial distribution.

Precipitation Trends over the Indus Basin

A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in such cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.

Hydrological response of Chamelia watershed in Mahakali Basin to climate change

Chamelia (catchment area = 1603 km²), a tributary of Mahakali, is a snow-fed watershed in Western Nepal. The watershed has 14 hydropower projects at various stages of development. This study simulated the current and future hydrological system of Chamelia using the Soil and Water Assessment Tool (SWAT). The model was calibrated for 2001-2007; validated for 2008-2013; and then applied to assess streamflow response to projected future climate scenarios. Multi-site calibration ensures that the model is capable of reproducing hydrological heterogeneity within the watershed. Current water balance above the Q120 hydrological station in the forms of precipitation, actual evapotranspiration (AET), and net water yield are 2469 mm, 381 mm and 1946 mm, respectively. Outputs of five Regional Climate Models (RCMs) under two representative concentration pathways (RCPs) for three future periods were considered for assessing climate change impacts. An ensemble of bias-corrected RCM projections showed that maximum temperature under RCP4.5 (RCP8.5) scenario for near-, mid-, and far-futures is projected to increase from the baseline by 0.9 °C (1.1 °C), 1.4 °C (2.1 °C), and 1.6 °C (3.4 °C), respectively. Minimum temperature for the same scenarios and future periods are projected to increase by 0.9 °C (1.2 °C), 1.6 °C (2.5 °C), and 2.0 °C (3.9 °C), respectively. Average annual precipitation under RCP4.5 (RCP8.5) scenario for near-, mid-, and far-futures are projected to increase by 10% (11%), 10% (15%), and 13% (15%), respectively. Based on the five RCMs considered, there is a high consensus for increase in temperature but higher uncertainty with respect to precipitations. Under these projected changes, average annual streamflow was simulated to increase gradually from the near to far future under both RCPs; for instance, by 8.2% in near-, 12.2% in mid-, and 15.0% in far-future under RCP4.5 scenarios. The results are useful for planning water infrastructure projects, in Chamelia and throughout the Mahakali basin, to ensure long-term sustainability under climate change.